[1]} present the first widely used neural abstractive summarizer. The summarizer utilizes a beam search algorithm to generate a summary word-by-word based on an attend-based feed-forward neural language model as
\(\begin{aligned}P_r(y_{i+1} | \mathbf {Y}_{C}, \mathcal {D}; \theta ) &\propto \exp {(\mathbf {Vh} + \mathbf {W} \cdot \text{Enc}(\mathbf {Y}_C, \mathcal {D}))}, \\\mathbf {h} &= \tanh \left( \mathbf {U} [\mathbf {E}\mathbf {y}_{i-C_1},...,\mathbf {E}\mathbf {y}_{i}] \right),\end{aligned}\) 
